Welcome to Health Business Matters, RSM's newest podcast. Hosted by the National Lead of our Health Services team, Peter Saccassan, this video podcast series is here to act as your guide to the fresh ideas, innovations and people currently shaping the Health Sector.
In the first episode of Health Business Matters, Peter Saccasan interviews Charlie Farah from Qlik (Analytics and Data Integration Platform) and Matt Cunneen from RSM Australia. They discuss how data analytics can provide critical insights to help health business practitioners identify the best decisions in health care organisations. These insights can inform your decisions regarding patient care, staffing levels and future planning, ensuring that resources are properly allocated to optimise outcomes.
Whether you’re a medical or allied health practice, specialist, pharmacy, manufacturer, aged care facility, member organisation, local health organisation, or government department – Health Services by RSM will meet all your advisory, compliance and risk management needs.
Need to discuss Health Services for your business? Contact your local RSM adviser today.
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Health Business & Technology Conference
Charlie Farah and Matt Cunneen will be presenting at the Health Business and Technology Conference 2022
Sydney - 10 October (Hilton Hotel) and Melbourne - 13 October (Grand Hyatt)
You might be able to see them in person, review the program and reserve a seat here.
[00:00:00] VO: At RSM, we bring advisory, compliance and risk management services to the health sector. We hope that like us, you like to hear about innovation, technology, and business. This is Health Business Matters.
Managing a healthcare organisation is a complex and demanding job. Data analytics lightens the load by providing the information needed to make the right decisions. Those insights can inform patient care, staffing levels, and future planning, ensuring that scarce resources are properly allocated.
Today we're talking with two data experts, Charlie Farrah, Senior Director Solutions and Value Acceleration for Qlik, where he spends his time assisting healthcare and public sector organisations on their data and analytics transformation journey. And also Matt Cunneen, Director of Data and Analytics at RSM Australia, whose team uses the Qlik platform effectively to take clients on that data journey.
Hi, and welcome to the very first episode of Health Business Matters from RSM Australia, which you can also watch on RSMs YouTube channel. I'm Peter Saccason, National Leader Health Services at RSM, where we have pulled together our expertise in health, across all our service lines, to bring expert advisory services to the health sector.
Qlik has some amazing insights it has publicly shared about healthcare. These range from identifying clinical variations- and understanding population health- through to patient experience, and of course the executive dashboard.
Charlie, what are the two questions you get asked the most when organisations start on this journey?
Thanks, Peter. The two most common questions are really, who else has done this and how long did it take?
The beauty about healthcare is that there's no such thing as plagiarism. Most healthcare organisations are willing to share their solutions to common challenges that other organisations are also facing. It's really about establishing a partnership with your solution provider to do a gap of roadmap and a pathway to success and long term success and sustainability.
I'd add to that, Charlie- I don't think you're exactly right. It's about taking a step and starting on the journey. And not trying to do everything at once.
You know, sometimes the old way was let's bring everything together. Let's bring a massive data warehouse and bring everything in, and it would run away and we wouldn't see them maybe for two years. We wouldn't get any value. We can't work that way today. We've gotta start to get value really quickly.
So let's just bite off a little chunk. Build that, prove that it works, prove that there's value, and then move on to the next step. So I think it's about really bringing that down and bringing the value really quickly to the organisation.
Well, obviously the world has changed with technology and health is no exception to this. Charlie, what do you see as pushing this explosion in analytics?
I think there are four main areas that we're seeing that are pushing the boundaries in analytics across healthcare organisations. One is obviously the rising costs, and not only the cost of supply and demand. But also the resources- so your workforce- and being conscious of the services you are providing and how you're gonna be able to maintain your profit margins or your validity across the space.
The other one is around the consumerization of data. We know most of the population these days are much more comfortable interacting, using data, using data to sort of drive decisions, understanding outcomes across organisations. But also from the user base within a hospital or a healthcare organisation.
Most people now want to interact with data when and where they want to, rather than having to rely on a system they have to have and log into once in a while. And the other area is really around the modernization and connectivity. It's really about the technology advancements in healthcare. Going from paper records, obviously now to more electronic user bases, IOT systems, and other bits and pieces of data is becoming much more available and much more prominent.
So it's really about how organisations can leverage those data assets to be able to drive new changes, new efficiencies, eliminate variation, and understand the whole story that lives within their data.
Thanks, Charlie. I mean, for me, modernization and connectivity is an issue where I see firstly pain with legacy systems and lots of them, especially in health. And progress!
The amazing range , of wearables now in the health space. Could you comment perhaps on how data analytics works to provide better healthcare? In both of these examples of where we see pain and progress.
Yeah, absolutely. And I think this is the most exciting part around healthcare, the prominence of wearable devices and IoT devices now, and how organisations, healthcare organisations can leverage those data assets to be able to provide more direct and proactive care and support to patients.
So there's just one example. For diabetes patients, often these people have to take a daily or multiple times, pin prick test to test their blood sugar levels. Now through this amazing software, the patient's able to take their pin prick test. That result is automatically flagged.
The data is programmed through a pipeline, through to a Qlik application. The doctor is able to generate some insights from that recent diagnostic. And they're able to determine and provide advice to the patient on whether or not their insulin levels are above or beyond a reasonable level. And they're able to give more direct advice around their sugar levels and programs that they need to undertake. So it's really about getting some real time data in a way that you're able to interact with patients in a much more streamlined, efficient way. To prevent them from coming into hospital as well.
So there's huge areas of advancement in this space. We see this around sleep apnea, diabetes, a lot of other areas around health and wellness. Providing more in tune and proactive data to patients to enable them to join that journey as well. To join on that conversation, that health pathway as well.
Thanks, Charlie. I mean, of course, the term data has moved a long way from being stuck in files, you know, on the shelf, to where it is today. Matt Cuneen, do you find in your work that organisations need to reeducate in and around data literacy and how do they go about it?
Yeah, thanks Peter. Yes, it's a really important factor, and one that is often overlooked in organisations. I find often, companies are spending a lot of time and money creating the dashboards or the visualizations, the analysis and the reporting, yet sadly the people who are within those organisations are not as data literate as they could be.
So data literacy is simply the ability to read, work with, analyze and argue with data. So essentially it's the language of data. And if we were to be efficient in our work life, it helps if we can all speak the same language. But with that, we need to go beyond some of the basics, where a lot of organisations stop today.
We need to go beyond simply sum of sales, average cost and the count of widgets that we've sold. [00:07:04] Now they're valid. We need to look at those. Absolutely. But imagine an organisation where you're looking at the correlations within your data or factors that might cause an outcome. You know, are your staff able to identify the signals that are in the data from all that white noise that might exist, especially with the ever increasing volume of data that we're presented with every day.
So if we can speak the same language and have the same understanding of what a measure, such as treatment costs or medical equipment utilization, mean then we can focus on making a decision based on that information rather than trying to discuss what the number actually means.
Certainly, the, the base point for the data journey. Matt, thanks for that.
Charlie and Matt, you both said to me that health organisations and companies are right into data in some way, some better than others. Matt, if I was a multi-practice group or a med tech or biotech company wanting to ramp up my data analytics, just where do we start?
Well, like with every journey, Peter, it starts with the first step and the step is to do something. Don't wait, don't pause, you know, start today. And one of the things that we do here at RSM is we have a concept that we call a day with your data.
And what we do is we say, bring all your reports that you've got. You've got Excel over here. You might have a report that comes out of another system here. Bring those all to a meeting, and we sit down and we discuss them. So show me what you do today, what work you've gotta put in to actually get that outcome. The manipulations, you do the cut and paste, the vlookup, whatever it might be to get your result.
And then show me what's working. What you like, what you don't like. And then if there was a magic wand and I could wave that magic wand, what was something you'd love to know that you've haven't been able to ever find out about your information and in your data?
And so, okay, let's take that. Where, how would we work that out? Where does that data reside? We go and we then focus on delivering a small proof of value where we actually go and try and answer that question. The one that you've never been able to answer before, let's tackle that one. Yeah. And we take that on and we show that in a really short space of time, we can actually get an answer to that question that you've always wanted.
So once we start there, we say, well, we've spent a day, imagine if we spent a week or we spent two weeks. Right? We could really move the needle. And so, it really is that thing about starting, taking a step and always trying to build on that. It's a continuous journey and one of continuous improvement.
Well that's great Matt. I mean, I think we'll call you the Data Genie though, and not the Fairy godmother. Ok. So once I've begun the journey, what follows from there in terms of change management?
Yeah, look, I think, you know, whilst.... In the end, this is a technology that we deliver. I've always said, having been in IT consulting for 20 plus years is it's actually a change management exercise as much it is as it is a technology. And we've gotta take the people along with us on that journey.
And so that means including them early on in the process, getting them to understand it, getting them to be involved in the data. Maybe they're the data stewards in a particular area and they've got to ensure that there's data quality. Of what's coming into the system. [00:10:33] And if you have the business users all involved in that along the way, then they're more likely to understand it, be a part of it, and use it in their daily life to help make those decisions that they're looking for.
I was just gonna add there, I think it's really, also about that communication, that really engagement with the business as well. That's a critical part to that change management process. There's no good as in being the BI team that's deciding what the business is gonna need or what they're gonna want to consume.
A chief executive environment I used to work in the health system said to me, "It's not about the killer applications, it's about the killer questions." So you really need to understand what questions people want to ask of them. To then go off and build that as well. So it's really about, you know, the whole adage of, you know, dragging a horse to water, but you can't make them drink.
Well, that's the same with analytics. You can build these beautiful applications, beautiful dashboards, really pretty visualizations. But if you're not asked, answering the question, or giving you the insights that business needs to transform, to change operations, to improve clinical practice, to redesign the pathways, then you are not doing the job.
So it's really important to engage the people on the front line to help design and drive the way the analytics and the insights are gonna be developed.
Yeah. One of my favorite questions, if you like, Charlie, and I like that" it's not killer applications about killer questions". Matt, I'd be looking at some of those reports that people put on the table and simply ask, why do we get this report?
And I think you'll find in, I'll say 50%, you might tell me it's more, the answer will be it's because we've always done it. So I think, with the education of people about data and just what's possible, I think that's a really big piece.
Yeah, can I just add to that as well? Peter, there was an example, from a pathology service, who were obviously very busy, processing the number of numerous, you know, thousands of pathology orders daily.
And when they did an analysis of what was actually, what reports were actually read by the clinician or logged into by the clinician, they found that there was maybe 35 to 40% of those reports weren't actually read or opened. Which means they weren't adding to the clinical decision making of that particular patient.
And that means that they, that was effectively an inefficient practice, not only for the pathologist time, but also from a cost of service and also the patient's inconvenience as well from having to be, you know, pricked and prodded all the time to pull out the pathology.
So it really goes down to that education, a feedback mechanism and a feedback loop back to the people on the, the frontline ordering the tests, but also educating them around the process and the bigger picture around, you know, if it's not adding clinical value or supporting your clinical decision making. Should we do this just because we've always done it this way?
So it's about using those insights to drive that conversation, to drive that feedback loop so people that become more aware and more conscious of their decisions and the impact down the line across the entire business.
We've got lots of data going on and there's, in every healthcare organisation, there's certainly an overload of data. People often talk about the concept of 'big data'. Charlie, what's your view about that?
To be honest, I actually don't think it's about big data anymore, and it's about wide data.
It's about connecting to multiple disparate data sources, external data sources, structured data sources, unstructured data sources. The wider the data, the more insight and correlations and active sort of intelligence that you can get from your data assets. It's really about being able to drive and see the whole story.
Cause context often matters in healthcare. There's no good in you just seeing and reviewing one simple data set. It's only when you can combine multiple data sets to see what levers or changes in one have an impact down the line on another.
An example is, some hospitals in the UK bringing weather data into their emergency department data, to see what the impact is gonna be on their patient flow and demand management.
So they can see based on historical data, whether it drops below a certain degree, they're gonna have a higher volume of older patients presented with respiratory illness. So from a planning perspective, they're able to predict and instill more, older or geriatricians or respiratory clinicians and it make sure the patient flow or demand management unit understands what the flow is gonna be. So they can free up some beds to make sure that they're still able to meet their targets.
Similarly, here in Australia, some organisations are using social media. To see when they make a change to a particular policy, particularly around like covid at the time, they can see what the social sentiment is around that data, whether people are willing or not willing to get vaccines, what their thoughts are around a particular vaccine, et cetera.
So as a service you can pivot and make changes to your programs or your strategy around that as well, but also your communication. So it's critical to start looking at the wider data sources and bringing those into your analyses to see how that's gonna drive changes and improvements.
I'm just wondering if either of you have the weirdest data set that you've ever dealt with, outside of the normal operating system.
Maybe if you can bring it to mind, that's great, or we'll take that question on notice and, and pop it to us further on in the conversation.
Actually, I've got an example there, Peter. There was one organisation out here in Western Sydney that started bringing in live traffic data into their database to start seeing how that impacted on no shows and people that canceled appointments in their clinics.
So there's just a variety of data and the talking about structured and unstructured data. There really is no limit with Qlik. It's about, you know, you're limited by your imagination rather than the data.
And I'll add one there too, which I thought was fascinating. Again, it was external data and I think this is a really important part for everyone to think about is not just what is internal to your organisation, but external data.
It was a freight company, and they brought in weather data, but they were looking at wind. And the impact that would have on their trucks as they traveled around the country, and therefore the costs of fuel.
And it made a serious impact if the wind was coming from certain directions on actually what their costs were. I thought that was a brilliant use, of, you know, taking data that's freely available and working out a way to save a dollar.
Okay. Look, I mean, medicines and procedures that we have today, they're multiplying exponentially. And they come from painstaking and often unseen research that is carried out in health. Charlie, how does data analytics contribute to this important part of the health site?
Oh, incredibly, Peter. I think, as you can imagine, the old methods of collecting data for research was quite cumbersome, challenging, timely.
You know, having to collect information either from a paper record and then translate it into an Excel file or some other database, took years and years. Whereas now, because the data is all readily available in these electronic systems, click enable, easily pull those bits elements out and, and provide that common picture to support the hypotheses really quickly. So rather than waiting, you know, years, you can often get insights in a matter of weeks, or months.
There's a particular example from the Sydney Local Health District here in New South Wales, around their lower back pain presentations to E.D. And their clinicians and researchers say that it's try and help them translate research from 15 years down to one or less.
Just by being able to use the data in a much more effective way, in a much more timely way to create that feedback loop back to the clinicians.
Well, hopefully that means we will all live longer than we think because they're finding new ways of keeping us alive. That's great. And Charlie, one day I see, with this data all being available, is that you end up with the treatment specialists stuck behind screens.
So what's the next step here to avoid that?
Yeah, I think the critical part there is being able to allow organisations and their workforce to self-serve. That means having access to the information at any time on any device really. There's some research from Gartner and others that suggests that people are 15 times more likely to use analytics when it's embedded into their workflow.
So to make it as efficient and as effective as possible for people to be able to interact with the analytics is a key component to that, rather than asking them to log in and log out of different systems. Having that embedded into their workflow is a key piece to having adoption. And then obviously the success that comes from that.
And a really easy example of that, Peter and Charlie, is alerting. Now, we all have apps. We've got lots of apps on our phone. You know, it's dinging all the time. Your watch is talking to you, saying get up and walk. You know, we're alerted all the time to things and it's quite a normal way for us to to respond.
Your analytics these days when you are loading data regularly can look for things that are important, and if they are something that you want to track, they can get an alert sent to you in the means that you like to, to then go and say, Right, I need to go look in something and take some action. So, you know, we've got the push capability in there, not just the pull.
And I think that's a really simple example of taking the analytics out to the user, rather than them coming in.
And I think what goes with that too, Matt, from what we were saying earlier, is that in the users of those alerts have to get their head around that, you know, these alerts are part of their day.
And oh, you know, I'll look at that later, which can be a reaction to some things that happen on our phone. And, obviously, it's a matter of saying, well, you don't have to go to the screen and look at it now, you can just wait for the alert and, and trust the system. So I think that's certainly, that whole education piece we were talking about is important.
Matt, just going back to our multi-site GP practices that we mentioned earlier, what's an example of some of a basic practical use of analytics in that sort of enterprise?
There's a lot. Certainly looking at patients and appointments and scheduling and understanding the capacity that you've got with your stuff to be able to handle those appointments.
And simple things like if people are canceling appointments. You know, why are they canceling? What are the reasons? Is it because they can't travel? Is it because they've got a particular illness? Do we need to look to have ways that they can use telehealth so that they can just dial it in?
Which a lot of GP clinics that I know are doing today, and should we be looking to uplift that more to allow us to service the people where they are?
I work with one allied health professional organisation and they're mobile. We go to you, you know, and they have been very, very popular. It's great with the aged care people and those on NDIS. You know, who have difficulty in getting to those facilities. And then if you look at the kind of treatments that you're providing, or the recommendations for the health outcomes based on how the people are presenting.
You know, if x amount of people are needing an X-ray, can you look somewhere in the middle of your GP clinics to set up an X-ray facility that's part of your overall practice where you can direct them there and add an extra level of care that's under your control. Maybe it's at the back. Maybe you have got room in your current practice and you can have an x-ray machine out there. Imagine you can walk straight out, have the x-ray, get back in front of the doctor within, you know, minutes.
And you can continue the care. That, often, can take two weeks. So I think some of those things are really practical ways that you can just see what else can we add here in the moment to be able to give better health outcomes for our patients.
That's a great example, Matt. I mean, I certainly find, we certainly find here at RSM that the other side of the coin there is, then having the owners take the time to assess that data and make decisions.
And we work with multiple GP practices to catch up with them regularly to go through their data and say, "Well, what does this mean for your business?"
Because we know that many of them don't have the time in their professional practice to look at the data and then make some decisions that are informed.
And again, another area of practice, of course, is getting a lot of airplay recently with aged care. The federal government has spent a lot of time, spending a lot of money in this area. And during Covid, of course, it became a real focus. With the aging population, the mere mention of age care will evoke a response and it will gain interest.
So Matt, how can aged care providers leverage data analytics to manage their facilities?
Well, Peter, it's a great question. And look, aged care facilities are always in the news, because it's people caring about people that we care about, our parents and our grandparents, you know? So it's obviously an emotional issue.
But there's an amazing amount that analytics can do here. You know, you could look at the type of incidents that are occurring or injuries, and these days this can be tracked automatically through what we call the internet of things. So you know, there can be pressure mats next to beds, for people who may have a fall out of that bed, and that information can be sent directly to those that need to go and deal with that situation.
Medication, you know, tracking that the medication is being used properly and effectively and timely. And then sharing that information with other healthcare providers. You know, getting external data in, as we say, or sharing that out to others. It can go to diet, it can go to meal plans. It really is endless, the way that data can help in aged care.
Simple things like occupancy of beds is something that is across all kind of healthcare facilities. Not just age, but then like a really key element to any organisation is also around workforce management and around staff. Just making sure you've got the right amount of staff. It doesn't matter what company I speak to on a daily basis, they're always gonna try and work out.
We need to make sure that we've got the right staffing levels and you know, for here, the staff to patients ratio are absolutely critical to ensuring that you can provide the quality of care that's required.
Just touching on one of Matt's comments around, you know, the sharing of data from aged care providers, whether internal or external.
I think that's really important. That's a new wave we are seeing in healthcare is that putting the patient at the center of the care rather than having to review all this information in isolation.
Whether they present to a GP practice, then in the aged care home, and then in the tertiary or secondary healthcare facility, like a hospital. It's about making a triangulation of that data so that information is shared, so people can leverage that information, leverage the learnings, leverage the insights, and come up with a common pathway or a treatment plan for that patient rather than doing things in isolation and potentially repeating and not being as efficient. It's using the data to drive change.
That's right Charlie, I think you've made a good point there about putting the patient in the center of the treatments. And I know I've worked with Matt together in the pharmacy space and everyone visits a pharmacy. And your local pharmacy has so much health data. With the growth in professional services, coming from the pharmacist and their heroic contribution to the covid frontline, there's so much information stored in the pharmacy patient database.
So for me, being a business advisor, it's interesting to see the correlation between say prescriptions and health products. The ranking of, of molecules prescribed, and what that indicates for likely professional services and health products in the pharmacy. Looking at the growth in particular health departments and the take up of professional services generally, and the beauty of technology today, of course, that we can bring together outside data and apply the different data sets against each other to generate trends in operational performance.
So for me, it takes pharmacy advice to a new and exciting level. But it also shows that data analytics can apply to health businesses from the smallest, right through to the largest.
We've spoken today already about getting started on the data journey. And change management. So, Matt, let me ask you, what has the availability of data and the power of analytics done in changing the way owners be they practitioners, privately owned companies, boards, or governments, how they make decisions?
Yeah, Peter, the availability of this data has really allowed the collective group of owners to pivot their organisations businesses to quickly respond to patient needs, consumer taste and public demand. And it's gone from being just a gut feel to being fact. And I think that's the really important thing.
You know your business, you sort of sense that things are happening, but if you actually can rely on the facts, then you can make better decisions. And it's also then the ability to look at things in a different way. You know, we spoke before about why. You know, the five year, the four year old question, Why?
Why are you doing that? You know, my five year old asks me that every day. Why dad? Why am I looking at that report? And if we always look at something the same way, we're only ever gonna see the same things. So often we need to just turn it slightly and look from a different angle. Let's come from the opposite direction.
We had this exact example last week I was presenting in Brisbane, and an organisation was looking at capacity based on one set of measures, and it said that they were running at 67% of utilization for their staff. When you actually got the time sheet data and looked at it from the opposite direction, they were running at 107% and they were servicing some customers by a factor of four to one.
Now, they thought they needed to go out and get more sales. Actually, what they needed to do is make sure they're being more efficient in who they were serving, and it was completely different coming from the other angle. And that's the thing that data and analytics brings to these owners and business owners and organisations today.
Well gents, one might put forward the proposition that the implementation of data analytics is in the end a tool. Making information available in better formats. We've spoken a lot today about applications and change management and the business and the patient care case for better data. Can you give us some takeaways for our listeners that can apply to all sizes of organisations?
Over to you, Charlie.
Yeah, thanks Peter. And there's no doubt that data analytics is an enabler. The technology's an enabler, but we really need the people and the processes across the organisation to be humming along nicely, to be able to make the most of those opportunities with the data. So I think the three main takeaways for me are really about sharing that data analysis across your organisation.
You know, we call it our self-serve that to really penetrate every line of business across the organisation to make the biggest impact. The second one is really to embed those data and decision making into workflow processes so people become in tune with using data as a day-to-day activity rather than it being a one off exercise once a week.
And the second one, uh, the last one really is about investing in the people to improve those processes. You know, taking them on that journey, showing them how to use the data, giving them the confidence to use and argue the data, to be able to make changes that are gonna affect their business.
Yeah. Thanks Peter. I think for me, no organisation is too small to benefit from starting a journey. You know, this isn't just for the big end of town. This is for everybody.
And I then urge you to start. Have a day with your data. See where that gold is within the data. And there's gold there within them hills. There really is. There always is.
And then thirdly, once you've started, keep going. Don't pause. This is a continuous improvement process to make sure that you want to keep fulfilling the outcomes for your patients and for your business.
Well, there you have it listeners. Three takeaways from each of our two guests today.
So thanks to Charlie Farrah from Qlik. And to Matt Cunneen from RSM who've been our special guests on this first episode of Health Business Matters.
All LinkedIn profiles and websites are available in our podcast description if you'd like to catch up with anyone on the show directly.
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